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Zhongwei Li
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templates/nextjs/tool-calling-route.ts
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325
templates/nextjs/tool-calling-route.ts
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/**
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* Next.js API Route with Tool Calling
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*
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* File: app/api/chat-with-tools/route.ts
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*
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* Demonstrates tool calling integration with TheSys C1.
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* Includes:
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* - Zod schema definitions
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* - Web search tool (Tavily)
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* - Product inventory tool
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* - Order creation tool
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* - Streaming with tool execution
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*/
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import { NextRequest, NextResponse } from "next/server";
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import OpenAI from "openai";
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import { z } from "zod";
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import zodToJsonSchema from "zod-to-json-schema";
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import { transformStream } from "@crayonai/stream";
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import { TavilySearchAPIClient } from "@tavily/core";
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const client = new OpenAI({
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baseURL: "https://api.thesys.dev/v1/embed",
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apiKey: process.env.THESYS_API_KEY,
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});
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const tavily = new TavilySearchAPIClient({
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apiKey: process.env.TAVILY_API_KEY || "",
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});
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// ============================================================================
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// Tool Schemas
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// ============================================================================
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const webSearchSchema = z.object({
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query: z.string().describe("The search query"),
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max_results: z
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.number()
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.int()
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.min(1)
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.max(10)
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.default(5)
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.describe("Maximum number of results"),
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});
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const productLookupSchema = z.object({
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product_type: z
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.enum(["gloves", "hat", "scarf", "all"])
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.optional()
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.describe("Type of product to lookup, or 'all' for everything"),
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});
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const orderItemSchema = z.discriminatedUnion("type", [
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z.object({
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type: z.literal("gloves"),
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size: z.enum(["S", "M", "L", "XL"]),
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color: z.string(),
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quantity: z.number().int().min(1),
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}),
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z.object({
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type: z.literal("hat"),
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style: z.enum(["beanie", "baseball", "fedora"]),
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color: z.string(),
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quantity: z.number().int().min(1),
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}),
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z.object({
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type: z.literal("scarf"),
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length: z.enum(["short", "medium", "long"]),
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material: z.enum(["wool", "cotton", "silk"]),
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quantity: z.number().int().min(1),
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}),
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]);
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const createOrderSchema = z.object({
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customer_email: z.string().email().describe("Customer email address"),
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items: z.array(orderItemSchema).min(1).describe("Items to order"),
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});
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// ============================================================================
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// Tool Definitions
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// ============================================================================
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const webSearchTool = {
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type: "function" as const,
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function: {
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name: "web_search",
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description: "Search the web for current information using Tavily API",
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parameters: zodToJsonSchema(webSearchSchema),
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},
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};
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const productLookupTool = {
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type: "function" as const,
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function: {
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name: "lookup_product",
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description: "Look up products in inventory",
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parameters: zodToJsonSchema(productLookupSchema),
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},
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};
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const createOrderTool = {
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type: "function" as const,
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function: {
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name: "create_order",
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description: "Create a new product order",
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parameters: zodToJsonSchema(createOrderSchema),
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},
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};
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// ============================================================================
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// Tool Execution Functions
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// ============================================================================
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async function executeWebSearch(args: z.infer<typeof webSearchSchema>) {
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const validated = webSearchSchema.parse(args);
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const results = await tavily.search(validated.query, {
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maxResults: validated.max_results,
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includeAnswer: true,
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});
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return {
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query: validated.query,
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answer: results.answer,
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results: results.results.map((r) => ({
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title: r.title,
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url: r.url,
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snippet: r.content,
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})),
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};
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}
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async function executeProductLookup(
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args: z.infer<typeof productLookupSchema>
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) {
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const validated = productLookupSchema.parse(args);
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// Mock inventory - replace with actual database query
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const inventory = {
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gloves: [
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{ id: 1, size: "M", color: "blue", price: 29.99, stock: 15 },
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{ id: 2, size: "L", color: "red", price: 29.99, stock: 8 },
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],
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hat: [
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{ id: 3, style: "beanie", color: "black", price: 19.99, stock: 20 },
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{ id: 4, style: "baseball", color: "navy", price: 24.99, stock: 12 },
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],
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scarf: [
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{ id: 5, length: "medium", material: "wool", price: 34.99, stock: 10 },
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],
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};
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if (validated.product_type && validated.product_type !== "all") {
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return {
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type: validated.product_type,
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products: inventory[validated.product_type],
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};
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}
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return { type: "all", inventory };
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}
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async function executeCreateOrder(args: z.infer<typeof createOrderSchema>) {
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const validated = createOrderSchema.parse(args);
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// Mock order creation - replace with actual database insert
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const orderId = `ORD-${Date.now()}`;
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// Simulate saving to database
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console.log("Creating order:", {
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orderId,
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customer: validated.customer_email,
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items: validated.items,
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});
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return {
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success: true,
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orderId,
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customer_email: validated.customer_email,
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items: validated.items,
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total: validated.items.reduce(
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(sum, item) => sum + item.quantity * 29.99,
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0
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), // Mock price
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message: `Order ${orderId} created successfully`,
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};
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}
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// ============================================================================
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// API Route Handler
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// ============================================================================
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export async function POST(req: NextRequest) {
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try {
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const { prompt, previousC1Response } = await req.json();
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if (!prompt || typeof prompt !== "string") {
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return NextResponse.json(
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{ error: "Invalid prompt" },
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{ status: 400 }
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);
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}
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const messages: OpenAI.Chat.ChatCompletionMessageParam[] = [
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{
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role: "system",
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content: `You are a helpful shopping assistant with access to tools.
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You can:
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1. Search the web for product information
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2. Look up products in our inventory
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3. Create orders for customers
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Always use tools when appropriate. Be friendly and helpful.`,
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},
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{ role: "user", content: prompt },
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];
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if (previousC1Response) {
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messages.splice(1, 0, {
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role: "assistant",
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content: previousC1Response,
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});
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}
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// Create streaming completion with tools
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const llmStream = await client.beta.chat.completions.runTools({
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model: "c1/anthropic/claude-sonnet-4/v-20250617",
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messages,
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stream: true,
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tools: [webSearchTool, productLookupTool, createOrderTool],
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toolChoice: "auto", // Let AI decide when to use tools
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temperature: 0.7,
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});
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// Handle tool execution
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llmStream.on("message", async (event) => {
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if (event.tool_calls) {
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for (const toolCall of event.tool_calls) {
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try {
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let result;
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switch (toolCall.function.name) {
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case "web_search":
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const searchArgs = JSON.parse(toolCall.function.arguments);
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result = await executeWebSearch(searchArgs);
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break;
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case "lookup_product":
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const lookupArgs = JSON.parse(toolCall.function.arguments);
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result = await executeProductLookup(lookupArgs);
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break;
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case "create_order":
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const orderArgs = JSON.parse(toolCall.function.arguments);
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result = await executeCreateOrder(orderArgs);
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break;
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default:
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throw new Error(`Unknown tool: ${toolCall.function.name}`);
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}
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console.log(`Tool ${toolCall.function.name} executed:`, result);
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// Tool results are automatically sent back to the LLM
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// by the runTools method
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} catch (error) {
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console.error(`Tool execution error:`, error);
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// Error will be sent back to LLM
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}
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}
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}
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});
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// Transform stream to C1 format
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const responseStream = transformStream(llmStream, (chunk) => {
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return chunk.choices[0]?.delta?.content || "";
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}) as ReadableStream<string>;
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return new NextResponse(responseStream, {
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headers: {
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"Content-Type": "text/event-stream",
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"Cache-Control": "no-cache, no-transform",
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"Connection": "keep-alive",
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"Access-Control-Allow-Origin": "*",
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},
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});
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} catch (error) {
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console.error("Chat API Error:", error);
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if (error instanceof z.ZodError) {
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return NextResponse.json(
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{
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error: "Validation error",
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details: error.errors,
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},
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{ status: 400 }
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);
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}
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if (error instanceof OpenAI.APIError) {
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return NextResponse.json(
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{
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error: error.message,
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type: error.type,
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},
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{ status: error.status || 500 }
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);
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}
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return NextResponse.json(
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{ error: "Internal server error" },
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{ status: 500 }
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);
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}
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}
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export async function OPTIONS() {
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return new NextResponse(null, {
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headers: {
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"Access-Control-Allow-Origin": "*",
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"Access-Control-Allow-Methods": "POST, OPTIONS",
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"Access-Control-Allow-Headers": "Content-Type",
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},
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});
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}
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